"""Do the paper's audio-side findings survive when the CONTEXT is heard too?

    python analysis/07_audio_context_study/02_replication.py
    python analysis/07_audio_context_study/02_replication.py --skip-models

The voice study swapped the voice and held everything else fixed. This study swaps
the modality of the conversation history: the same 30 prompts are rated with
the history read (the original study) or heard, either in one voice for both
speakers (B1) or with a distinct voice per speaker (B2).

Every metric is the one _voice_variation_replication.py computes -- imported from there
rather than reimplemented, so the two studies cannot drift apart in how a
threshold or an ICC is defined. The only differences are which long tables get
loaded and which prompt set the reference arms are restricted to (the 30
context prompts, not the 30 voice prompts).

B1 is the conservative cell: context modality changes, voice identity does not.
B2 adds a second speaker. Reading B2 against B1 rather than against the text
baseline is what separates speaker differentiation from audio context itself.
"""

# Implementation lives in _audio_context_replication.py, which other analyses import.
import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "common"))

from _audio_context_replication import main  # noqa: E402

if __name__ == "__main__":
    main()